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GNSS researchers are presenting hundreds of papers at the 2022 Institute of Navigation (ION) GNSS+ conference, taking place Sept. 19–23 in Denver, Colorado, and virtually. The following five papers focus on GNSS receiver technology and interference mitigation. The papers will be available at www.ion.org/publications/browse.cfm.
FINDING INTERFERENCE WITH ADS-B
Conference Presentation: Sept. 23, 1:50 p.m.; Session F6
The growing dependence of critical and safety-of-life systems on GNSS makes the ability to rapidly detect and localize the presence of GNSS interference events increasingly important. Ground-based GNSS jammer detection can be used to detect local interference sources. However, this approach is limited by line of sight, hence applying it to large areas is costly in both time and money.
A complementary technique is to use the airborne GNSS receiver data provided by Automatic Dependent Surveillance—Broadcast (ADS-B). As these receivers are at altitude, their lines of sight can cover a wide area. The drawback is that ADS-B was not designed for this purpose, and the messages contain limited information for the assessment of interference.
The authors have developed and will demonstrate an algorithm for real-time detection and localization of GNSS interference sources using ADS-B transmissions on the 1090 MHz (Mode S ES) radio frequency channel. They demonstrate this capability using recorded ADS-B transmissions from known interference events.
Zixi Liu, Sherman Lo, Todd Walter, Juan Blanch, Stanford University; “Real-time Detection and Localization of GNSS Interference Source.”
TESTING A GNSS MONITORING SYSTEM
Conference Presentation: Sept. 23, 4:04 p.m.; Session F6
Even interference at low levels can be catastrophic to systems that depend on GNSS. It can prevent GNSS signals from reaching the user (interference or jamming) or give false signals, resulting in an incorrect position and time solution (spoofing). The capability to confidently detect and localize interference quickly could help mitigate this threat. Furthermore, if the system could also provide information characterizing the interference, it could help law enforcement not only interdict, but also prosecute the threat.
Building a consumer-level commercial-off-the-shelf (COTS) GNSS monitor would also make it cost effective for widespread utilization. This paper describes the development and field testing of a system to provide this capability.
The monitor uses the u-blox F9, an inexpensive commercial receiver offering multi-constellation and dual-frequency position and time solutions, as well as powerful interference-detection metrics. Initial analysis of the receiver’s measurement capabilities determined that it provides many features useful for assessing the operational environment across a geographical region. Performance and output of the receiver is characterized under different jamming and spoofing scenarios.
Different receivers and antennas may react differently based on both hardware and software configurations and offer the user varying interference rejection techniques and detection metrics. As a result, it is important to gain a good understanding of the receiver’s behavior. Another way to test behavior is to examine its performance in nominal conditions in various scenarios and locations, as presented in this paper.
Benon Gattis, Dennis Akos, University of Colorado Boulder; Yu-Hsuan Chen, Sherman Lo, Todd Walter, Stanford University; “Test and Measurements from a Global Navigation Satellite System (GNSS) Monitoring System.”
GEOLOCATING INTERFERENCE WITH SMARTPHONES
Conference Presentation: Virtual; Session F6
With the availability of RAW GNSS measurements on Android smartphones, detecting GNSS interference using modern handsets has become a realistic crowdsourcing possibility, especially with the inclusion of automatic gain control (AGC) in Android 8 (Oreo).
While crowdsourcing jamming detection — and knowing whether your smartphone is subject to jamming or spoofing — is valuable, locating the interference source may be even more important. This work explores the feasibility of crowdsourcing interference source localization with modern Android smartphones.
The work has three goals:
- To examine localization of a civilian-type GPS L1 jammer using a network of smartphones
- To investigate how best to approach current obstacles regarding such localization
- To estimate how accurate this type of positioning can be.
An important part of this work is to investigate differences in GNSS data reported by various Android smartphones. The smartphones in this study were specifically selected by the manufacturer of the GNSS chipset to enable the authors to examine how their GNSS receivers perform under the same circumstances. Three parameters were specifically investigated as measures of received jamming power: carrier-to-noise ratio (C/N0), AGC and the number of tracked satellites.
The selected smartphones were put through a series of tests to examine how these three parameters vary with changing conditions. These tests include subjecting the smartphones to an actual jammer in a controlled lab setup and an investigation of the impact of smartphone (GNSS antenna) position and orientation on C/N0 and AGC. Using the data collected in these tests, several interference geolocation strategies will be discussed.
The authors also consider whether interference localization from consumer-off-the-shelf (COTS) smartphones is currently accurate enough for this use. The shortcomings of smartphone GNSS hardware may be resolved using more clever positioning strategies such as using a larger number of handsets. Alternatively, it may require upgraded hardware and standardization.
Søren Skaarup Larsen, Daniel Haugård Olesen, Anna B. O. Jensen, Lars Stenseng, Technical University of Denmark, DTU Space; “Assessment of RFI Geolocation Using Modern Android Smartphones.”
MITIGATING MULTIPATH IN AN L5 CHANNEL
Conference Presentation: Sep. 21, 4 p.m.; Session F2
Multipath mitigation with machine learning relies on offline training with an exhaustive number of labeled observations. Current super-resolution correlation methods, which include MUltiple SIgnal Classification (MUSIC), operate online by testing and choosing from a high number of candidate signal hypotheses.
A new method of MUSIC is presented that reduces numerical complexity and is applied to processing L5 correlation vectors to reduce multipath by identifying the earliest path. The rank of this estimator is examined in static and dynamic conditions in various signal environments. Higher rank allows more signal paths to be identified.
This method is also complementary with various L5 signal-tracking methods such as open- and closed-loop tracking.
Paul McBurney, Norman Krasner, Florean Curticapean, Miguel Ribot, Mahdi Maaref and Lionel Garin, OneNav; “Application of Super Resolution Correlation to Multipath Mitigation in an L5 Channel.”
USING A VIRTUAL ANTENNA ARRAY
Conference Presentation: Sep. 22, 11:03 a.m.: Session F3
One of the simplest ways to increase GNSS anti-jamming and anti-spoofing (AJ/AS) performance is increasing the number of controlled reception pattern antenna (CRPA) array elements. However, this increases the size, cost, complexity and required processing power of the overall system. To counter this constraint, the researchers applied a new development in antenna hardware design to GNSS threat mitigation techniques. This resulted in better CRPA performance without increasing the footprint. The work improves AJ/AS performance without adding additional elements, and serves as proof of concept of the application of an adaptively spaced virtual array created with multimodal elements to GNSS AJ/AS.
New breakthroughs in antenna-array research extend the case of non-uniform excitation of elements to the elements’ individual positions. By using multimodal antennas as elements, it has been shown that elements’ phase centers, or perceived locations, can be adjusted with purely electronic means. When applied to each element in an antenna array, this realizes a reconfigurable array.
This research extends the concept of a virtual array with adaptive inter-element spacing into GNSS AJ/AJ methods. A new way to integrate a virtual array into a GNSS application is explored and incorporated into current space-time adaptive processing (STAP) algorithms.
Gabriel Wiggins and Scott Martin, Auburn University; “Applications of a Virtual Antenna Array to GNSS Threat Mitigation: First Results.”
